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$4.3 per dollar spent. The study focused their estimates of SSI costs and intervention effects on specific departments that were targeted with quality improvement initiatives.7 The difference in their estimates can be attributed to the higher attributed cost of SSI and added benefits from reductions in UTI and blood transfusions, which increases the potential benefit of the inter- vention, as well as focusing on priority departments. As our study has shown, departmental returns on investment can vary dramatically. Our findings are well complimented in showing that NSQIP, in combination with well-designed quality improvement initiatives, is likely to produce positive returns on investment. Our study is the first to perform a cost analysis with a detailed


and generalizable methodology for calculating the cost of an SSI that incorporates the costs of both NSQIP and the associated quality improvement program interventions, and presents results at the departmental level. We also introduce the potential of a ROI frontier curve, which we believe is a valuable decision- making tool for other hospitals to consider. Our study has 2 notable limitations in the study and model


design. The first is that by using aggregate-level information from the hospital, we have high uncertainty in the outcomes, primarily driven by the estimated per-patient cost of SSI. Although we present a full analysis that includes the statistical uncertainty from the available data, the extreme range of potential costs of SSI may not be a reasonable reflection of the cost of SSI that we would see if we controlled for other confounding factors such as patient characteristics, SSI severity, and type of surgery (eg, differentiat- ing by urgent or elective surgery). The second limitation is that we cannot reasonably estimate the


attributable effect of quality improvement programs such as CUSP on SSI incidence. It is possible that exogenous effects such as improved staff experience, change in patient safety culture, improvements in surgery techniques that are less invasive, changes in hospital infrastructure, and unknown ad hoc initiatives have some impact on overall SSI incidence. To address this limitation, we conducted a scenario analysis that considers all possible attri- butable effects of SSI incidence on the hospital’s ROI. The ROI frontier curve can be a valuable decision-making tool for estimating the target SSI incidence change necessary for the current annual investment to offer a positive return to the institution. This study has some limitations. The ROI estimates observed


in this study may not be easily generalizable to other hospitals due to standard eccentricities of a given hospital’s operations, internal costs, and the suite of interventions they select to implement. The methodological approach, however, was designed to apply a return on investment framework to any Canadian hospital setting in a manner that is replicable and generalizable to the question and available data. In conclusion, this study shows how an institutional return on investment framework can be applied to quality improvement initiatives at a hospital. The investments in NSQIP and CUSP to date at TOH likely have a substantial positive return on invest- ment of US$3.07 for every dollar invested, though the ROI esti- mates rest on several assumptions, primarily the cost of an SSI case and share of incidence reduction attributable to NSQIP. Although this study does present useful methods for evaluating return on investment in the face of this limitation, decision


Sasha van Katwyk et al


makers should encourage a rigorous program evaluation of the costs and attributable effectiveness of the quality improvement initiatives to ensure that such initiatives are improving the quality of care and continue to provide positive return on investment.


Acknowledgments. We thank Deanna Rothwell, the Manager of Perfor- mance Measurement at The Ottawa Hospital for providing data required for this study. We also wish to thank all reviewers for their insightful comments on the manuscript.


Financial support. This study was funded by Health Quality Ontario.


Conflicts of interest. All authors report no conflicts of interest relevant to this article.


References


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2. The Ottawa Hospital Data Warehouse. National Surgical Quality Improvement Program (NSQIP) data repository. Accessed August 2015.


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12. McNelis J, Castaldi M. ‘The National Surgery Quality Improvement Project’ (NSQIP): a new tool to increase patient safety and cost efficiency in a surgical intensive care unit. Patient Saf Surg 2014;8:19.


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14. Ontario Case Costing Guide, version 9.0. Toronto: Data Standards Unit, Health Data Branch, Ministry of Health and Long-Term Care; 2014.


15. Canadian Patient Cost Database technical document: MIS patient costing methodology, March 2017. Ottawa: Canadian Institute for Health Information; 2017.


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